Wearable Functional Ultrasound Device Concept

Functional ultrasound (fUS) is brain imaging technology which uses ultrasound imaging to detect movement of blood in the brain, which can be used to make a functional image. It has the combined advantages of EEG and fMRI processes, allowing for both high temporal and spatial resolution (Macé et al., 2011).

In general, ultrasound imaging techniques work by transmitting ultrasound waves to tissues in the body and detecting the changes in the echoes of the waves which bounce back. In fUS, this technique is optimized for detecting changes in cerebral blood flow. If a brain area is more active, it will require more glucose and oxygen, which must be carried to it by blood. Therefore, increased activity in a brain region will require increased blood flow to that region. Using fUS, blood flow to distinct regions can be measured and used to infer which brain areas were more or less active during a period of time (Macé et al., 2013).

This follows a similar idea to fMRI, which measures the amount of oxygenated and deoxygenated blood in distinct brain areas. However, fUS has many advantages over fMRI, since it is less expensive, does not require intense magnetic fields, and has much better temporal resolution (Zheng et al., 2023). Furthermore, fMRI machines are huge and noisy, and contain extremely strong magnets. Making this into a wearable technology would be very difficult, especially because of the strong magnets involved.

Throughout our examination of wearable neuroimaging technology in this course, we have mainly discussed and used Muse headsets, which utilize EEG and fNIRS. This technology is very portable and can be useful for many applications, but I feel that it is limited by the fact that it has very low spatial resolution. Techniques like EEG measure whole-brain activity in real-time, which make it very useful for neurofeedback applications. However, it is impossible to isolate and compare activity in different brain regions using this approach.

I believe that fUS presents an opportunity to combine the benefits of EEG and fMRI technology into a portable, wearable system. This would be transformative because it would allow for region-specific insights into brain activity in daily life, allowing for much more precise and useful brain data to be recorded by users. It would also allow for researchers to gain region-specific brain data without the requirement of large in-lab machinery, opening the door to many different kinds of studies which were previously not possible. Naturalistic studies in humans using fUS imaging have already been done, but required the device to be physically implanted beneath the skull (Soloukey et al., 2025). Creating a non-invasive wearable device would allow these same methods to be replicated in a broader sample of people.

As brain-imaging technology, fUS has proven very effective. For example, a study by Imbault et al. (2017) showed the usefulness of fUS during brain surgery. Furthermore, existing products show potential for fUS as a portable technology. With that being said, there are some severe limitations which currently make this technology lab- and clinic-bound.

Butterfly IQ is a portable ultrasound technology which plugs directly into any smartphone, and can image blood flow under the surface of the skin, which is useful for a variety of diagnoses. This product proves that ultrasound technology can be made portable. However, this technology, and ultrasound technology in general, is not strong enough to penetrate through the skull and image brain tissue. In general, ultrasound waves tend to be reflected and attenuated by the dense skull bone. This is the major obstacle in using ultrasound in brain imaging. In fUS brain imaging studies in rodents, this is typically overcome by surgically preparing an opening into the animal's brain, allowing for the ultrasound to easily penetrate into the skull (for example, Norman et al., 2021). This means that ultrasound can be used very effectively during human brain surgeries, as mentioned before, since the skull is already open. However, this would obviously not be an ideal solution for a portable human brain imaging device, as it is very invasive.

One example of an existing solution to skull penetration is Transcranial Doppler ultrasound (TCD), which takes advantage of existing “windows” into the brain where the skull is thinner in order to measure blood flow of major brain arteries. This device is useful in diagnosing certain types of stroke (D'Andrea et al., 2016). One common skull region utilized for TCD are the temporal windows, the flat regions of the skull in front of the ear (the “temples”) which are thinner than the surrounding skull. I pasted two images from this paper by D’Andrea et al. below, the first is a diagram of the temporal window scan and the second is the “color Doppler study” in this location.

The proposed technology would be a wearable functional ultrasound (fUS) headset capable of monitoring cerebral blood flow in real time through the temporal and occipital acoustic windows. These are two of the same skull openings used in traditional TCD systems, where the bone is thinnest and ultrasound waves can pass through with minimal attenuation (D’Andrea et al., 2016). Unlike TCD, this system would be optimized for fUS imaging as described by Mace et al. (2013).

The design would include two temporal transducer arrays, positioned just above each ear, and a smaller occipital array at the back of the head. These sensors would be embedded into a flexible, lightweight headband or helmet structure, similar to consumer EEG headsets.

Power would be supplied by a rechargeable lithium battery integrated into the rear of the headset. Data could be transmitted wirelessly to a smartphone or tablet, which would compute the data into an interactive brain image.

Below are some AI-generated images of the potential design of the headset.

Developing a wearable functional ultrasound (fUS) headset presents several key technical challenges. The most significant are penetrating through the skull, computational reconstruction of weak signals, and a light-weight, power efficient design. Each of these issues must be addressed to make the system both scientifically valid and practical for everyday use.

As stated before the most fundamental challenge is the attenuation and distortion of ultrasound waves by the skull. To address this, the headset would align transducers to the temporal and occipital acoustic windows, which are natural openings where the skull is thinner (D’Andrea et al., 2016). This would help get better penetration into the skull, but the signal would still be much weaker and noisier than an fUS scan where the skull is removed, which leads to the second challenge.

A second challenge lies in the computational complexity of reconstructing functional images from noisy, partial data. Through the skull, the returning ultrasound echoes will be weaker and more distorted than in a controlled laboratory environment where a section of the skull is removed. To maintain image quality, the headset would rely on AI-driven signal reconstruction methods. Neural network architectures trained on large datasets of simulated or empirical fUS recordings could learn to infer high-resolution activation maps from sparse or noisy input data (Demené et al., 2015; Zheng et al., 2023). This approach has already shown promise in ultrasound image denoising and super-resolution Doppler reconstruction.

The final challenge lies in turning this technology into a portable, power efficient design. The main solution here would be to use Bluetooth to send the data to a nearby computer or smartphone, rather than processing it in the machine. By offloading the bulk of this computation to a smartphone or computer, the headset itself can remain lightweight and energy-efficient while still producing meaningful, high-quality functional data.

A wearable functional ultrasound (fUS) headset could have a transformative impact on both neuroscience research and real-world applications. At present, functional neuroimaging is restricted to controlled laboratory environments due to the size, cost, and operational complexity of systems like fMRI. A portable fUS device would allow for region-specific brain imaging in naturalistic settings, enabling researchers to study cognition, emotion, and attention as they occur during daily life, without invasive methods. Clinically, it could support new methods for stroke monitoring, neurorehabilitation, and early detection of cerebrovascular disorders outside of hospital settings. For consumers, it could offer a way to monitor brain activity patterns during various tasks, providing feedback that goes beyond the surface-level activity signals offered by EEG-based devices.

In terms of timeline, an early prototype could likely be developed within five years, given that most of the enabling technologies already exist in medical and research contexts (Imbault et al., 2017; Zheng et al., 2023).

Over the past decade, ultrafast Doppler fUS has demonstrated the ability to resolve microvascular blood flow at tens of microns of spatial precision and millisecond temporal scales (Mace et al., 2011). At the same time, portable ultrasound electronics have evolved dramatically, as shown by systems such as the Butterfly iQ. However, the main feasibility concern of this technology would be whether it can penetrate the brain. My proposed solution is to place transducers on thin brain areas, such as the temporal windows (D’Andrea et al., 2016). However, it is possible that this is not adequate, and further innovation or invasive surgeries might be required in order to take fUS technology outside the lab.

The portable headset would aim for a cost range of $200-$1000, comparable to other portable brain scanning technology such as the Muse headsets. Ideally, they would be significantly cheaper than fMRI scanners or high-end lab equipment. Validation would involve a series of cross-modality studies, where images from the portable fUS are compared to those from laboratory fUS or fMRI during controlled cognitive tasks. Establishing correlations between activation maps and behavioral outcomes would demonstrate scientific validity and enable regulatory approval for research and clinical use.